• Lecture 1: Review of basic concepts of algorithms and complexity, probability and tail bounds. (pptx, pdf).
  • Further reading: There are a number of standard textbooks on algorithms, such as CLRS, KT and DPV. Introduction to probability from computer science perspective can be found in textbook MU and MR.
• Lecture 2: Linear program. Examples, Simplex algorithms, primal-dual, strong duality (and a physical interpretation), application to games. (pptx, pdf).
  • Further reading: Matoušek and Gärtner has a nice textbook on LP. For general (convex) optimization, please refer to this book by Boyd and Vandenberghe.
• Lecture 3: Algorithms for data streams. k-missing numbers, count-min sketch, lower bounds via communication complexity. (pptx, pdf).
  • Further reading:  Muthu Muthukrishnan has a page for streaming algorithms, including information about his book on the subject.
• Lecture 4: Approximation algorithms. Max-3SAT by random assignment, Vertex Cover by LP rounding, Set Cover by greedy, st-min-cut by randomized rounding. (pptx, pdf)
  • Further reading: A standard textbook for approximation algorithms is here by Vazirani. A more recent one, by Williamson and Shmoys, is available online here.
• Lecture 5: NP-Complete problems: NP, examples problems, NP-completeness, reduction. (pptx, pdf)
  • Further reading: See the wiki page for a list of commonly seen NP-complete problems related to graphs, strings, numbers, games, and many others.
• Lecture 6: Algorithms for resource allocation. Cake cutting, assignment game. (pptx, pdf)
  • Further reading: Here is a survey for cake cutting, and assignment game can be found in Chapter 8 of this book.
• Lecture 7: Stable matching.Gale-Shapley algorithm. Men/Women-optimal solution, quadratic lower bound. (pptx, pdf)
  • Further reading: Stable matching is a well-studied topic with rich structures and results. The textbook by Kleinberg and Tardos also has a related chapter about Stable Matching. The lower bound is from this paper.
• Lecture 8: Mechanism design. Social welfare and social choice. Second price auction and VCG. (pptx, pdf)
  • Further reading: A good textbook by Nisan, Roughgarden, Tardos, Vazirani on algorithmic game theory is available online here.
• Lecture 9: Online algorithm. Secretary problem. Ski-rental problem. Deterministic 2-competitive and randomized 1.58-competitive algorithms. (pptx, pdf)
  • Further reading: See this survey by Buchbinder and Naor about designing online algorithms via a primal-dual approach. See wikipedia page for the Secretary problem.
• Lecture 10: Online learning. Expert problem. Multi-armed bandit.(pptx, pdf)
  • Further reading: See a survey by Arora, Hazan and Kale on multiplicative weight update method. The book by Bubeck and Cesa-Bianchi gives a comprehensive treatment of the MAB problems.
• Lecture 11 (Note: venue changed to YIA 404 on CUHK campus): Influence maximization on social network. (1-1/e)-approximation algorithm using submodularity of spread function in IC and LT models. (pptx, pdf)
  • Further reading: See a survey by Chen, Lakshmanan and Castillo on influence propagation on social networks.
• Lecture 12 (Note: venue changed to YIA 404 on CUHK campus and time changed to Dec 1st): Quantum computing. Quantum algorithms, BQP, quantum non-locality, quantum games. (pptx, pdf)
  • Further reading: The Nielsen-Chuang is a nice book for beginners. See many references in the slides for more specific topics.

Note:

1. This is a tentative plan, subject to changes based on the pace of the class.
2. Slides (in pptx and pdf) will be posted usually one day before the class, and may be slightly updated right after the class. Open .pptx files using Microsoft Powerpoint (Office version 2010 or later).
3. The "Further reading" part is for your interest and reference only.